Quarterly profits in the banking sector

banks.R

library(tidyverse)
library(oenb)
library(colorspace)
library(futurevisions)

# Load data on quarterly profits in the banking sector
data <- oenb_data(id = "3104", pos = "VDBKICBD66EL210") |> 
  select(period, value) |> 
  as_tibble()

# Reshape the data
quarterly <- data |> filter(str_detect(period, "-")) |> 
  mutate(period = yq(period),
         year = year(period)) |> 
  mutate(qval = value - lag(value), .by = year,
         qval = ifelse(is.na(qval), value, qval))

# Define the number of rows and calculate the required number of columns
rows <- 5
cols <- ceiling(nrow(quarterly)/rows)

# Define the position within the grid and add information for the curves between the rows
plotdat <- quarterly |> filter(year >= 2015) |> 
  mutate(quarter = quarter(period),
         col = rep(c(seq(1,cols,1), seq(cols,1,-1)), rows)[1:n()],
         row = rep(1:rows, each = cols)[1:n()],
         c2row = ifelse(row != lead(row), lead(row), NA),
         c2col = ifelse(row != lead(row), lead(col), NA),
         end = ifelse(rows %% 2 == 0 & period == max(period), col-1, col+1)) 
  
plotdat |> ggplot(aes(x = col, y = row)) +
  geom_curve(aes(xend = c2col, yend = c2row), curvature = -1,
             data = ~. |> filter(!is.na(c2col), col != 1), 
             linewidth = 2, color = "gray85") +
  geom_curve(aes(xend = c2col, yend = c2row), curvature = 1,
             data = ~. |> filter(!is.na(c2col), col == 1), 
             linewidth = 2, color = "gray85") +
  geom_line(aes(group = row), linewidth = 2, color = "gray85") +
  geom_segment(aes(x = col, y = row, xend = end, yend = row),
           arrow = arrow(type = "closed", length = unit(8, "pt")),
           data = ~. |> slice_max(period),
           linewidth = 2, color = "gray85") + 
  geom_point(aes(size = qval, color = factor(year))) +
  geom_text(aes(label = year),
            size = 3, nudge_y = 0.4, family = "Roboto Condensed",  
            data = ~. |> filter(quarter == 1)) +
  geom_text(aes(label = scales::number(qval, scale = 1/1e3, accuracy = .1)),
            size = 2.5, family = "Roboto Condensed", color = "white",
            data = ~. |> filter(qval > 400)) + 
  scale_size_continuous(range = c(1, 18)) +
  scale_y_reverse(expand = c(0.1, 0.1)) +
  scale_x_continuous(expand = c(0.1, 0.1)) +
  scale_color_manual(values = c(futurevisions("cancri", ids = -6), futurevisions("europa", ids = 4:1))) +
  coord_cartesian() +
  labs(x = NULL, y = NULL, 
       title = toupper("Bankengewinne"),
       subtitle = "Quartalsgewinne des Bankensektors in Mrd. Euro\nQuelle: OeNB. Grafik: @matschnetzer") +
  theme_void() +
  theme(legend.position = "none",
        plot.title.position = "plot",
        plot.title = element_text(hjust = 0.5, family = "Roboto Condensed", size = 15),
        plot.subtitle = element_text(hjust = 0.5, family = "Roboto Condensed", size = 8, lineheight = 1.1))